Paternalistic Interventions: Determinants of Demand and Supply

Last registered on April 27, 2025

View Trial History

Pre-Trial

Trial Information

General Information

Title

Paternalistic Interventions: Determinants of Demand and Supply

RCT ID

AEARCTR-0007108

Initial registration date

February 16, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

February 16, 2024, 4:33 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated

April 27, 2025, 1:05 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

United States of America

Region

Primary Investigator

Name

Krishna Srinivasan

Affiliation

UniDistance Suisse

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Bjoern Bartling

PI Affiliation

University of Zurich

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2024-02-21

End date

2025-02-21

Keywords

Behavior, Governance, Welfare

Additional Keywords

Paternalism; paternalistic interventions

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Interventions by governments, experts, and parents in the lives of others are commonly motivated by a desire to help. What factors influence individuals’ willingness to intervene in the decisions made by others? What factors influence individuals’ attitudes toward paternalistic interventions imposed upon them? We conduct an experiment in a general population sample of the U.S. to address these questions.

External Link(s)

Registration Citation

Citation

Bartling, Bjoern and Krishna Srinivasan. 2025. "Paternalistic Interventions: Determinants of Demand and Supply." AEA RCT Registry. April 27. https://doi.org/10.1257/rct.7108-1.1

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention (Hidden)

Intervention Start Date

2024-02-21

Intervention End Date

2025-02-21

Primary Outcomes

Primary Outcomes (end points)

Key outcome for Choosers: Fraction of Choosers demanding an intervention. Key outcome for Choice Architects: Fraction of Choice Architects supplying an intervention. See the pre-analysis plan for more details.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

We randomly assign study participants to either the role of a “Chooser” or a “Choice Architect.” Each Chooser is randomly paired with a Choice Architect. The Chooser is tasked with selecting between two bonus options. To introduce potential decision-making errors, one bonus option is presented transparently, while the other bonus option is obscured, increasing the likelihood of the Chooser selecting the lower bonus. The Choice Architect has the opportunity to intervene in the Chooser’s decision to assist them in securing the higher bonus. We randomize study participants into one of six treatments in a 3 x 2 design. See the pre-analysis plan for more details.

Experimental Design Details

We randomize study participants into one of six treatments in a 2 x 3 factorial design. The first treatment dimension manipulates the restrictiveness of the intervention. In treatments Soft, the Choice Architect can inform the Chooser of the higher bonus and offer them the opportunity to revise their choice. Within treatments Hard, the Choice Architect can override the Chooser’s initial choice and select the higher bonus on their behalf, which constitutes the more restrictive intervention.

The second treatment dimension encompasses variations in whether a Choice Architect is informed of a Chooser’s preferences favoring or opposing an intervention (Preference Info and Consent Rights) or not (No Info), as well as whether a Chooser has the right to withhold consent to an intervention (Consent Rights) or not (No Info and Preference Info).

Randomization Method

Software-based randomization (Qualtrics)

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Sample size: planned number of observations

4000 participants in the role of Choosers and 4000 participants in the role of Choice Architects.

Sample size (or number of clusters) by treatment arms

500 pairs of participants in the Soft x No Info and Hard x No Info treatments and 750 pairs in each of the other four treatments.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

The Minimum Detectable Effect Sizes regarding our main hypotheses range from 5.1 to 8.9 percentage points. See the pre-analysis plan for more details.

Supporting Documents and Materials

IRB